Efficient Technique for Facial Image Recognition With Support Vector Machines in 2D Images With Cross-validation in Matlab-Reference-Cited by-同舟云学术

Efficient Technique for Facial Image Recognition With Support Vector Machines in 2D Images With Cross-validation in Matlab

Published:2020-05-07 Issue: Volume:15 Page:175-183
ISSN:1991-8763
Container-title:WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
language:en
Short-container-title:

Author:

Cadena Moreano Jose Augusto¹,La Serna Palomino Nora Bertha¹

Affiliation:

1. Facultad de Ingeniería de Sistemas e Informática, Universidad Nacional Mayor “San Marcos”, Lima, PERU

Abstract

This article presented in the context of 2D global facial recognition, using Gabor Wavelet's feature extraction algorithms, and facial recognition Support Vector Machines (SVM), the latter incorporating the kernel functions: linear, cubic and Gaussian. The models generated by these kernels were validated by the cross validation technique through the Matlab application. The objective is to observe the results of facial recognition in each case. An efficient technique is proposed that includes the mentioned algorithms for a database of 2D images. The technique has been processed in its training and testing phases, for the facial image databases FERET [1] and MUCT [2], and the models generated by the technique allowed to perform the tests, whose results achieved a facial recognition of individuals over 96%.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

Artificial Intelligence,General Mathematics,Control and Systems Engineering

Reference23 articles.

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